Major advances in genome science and molecular technologies provide new opportunities at the interface between basic biological research and medical practice. The unprecedented completeness, accuracy, and volume of genomic and molecular data necessitate a new kind of computational biology for translational research. Key challenges are standardization of data capture and communication, organization of easily accessible repositories, and algorithms for integrated analysis based on heterogeneous sources of information. Also required are new ways of using complementary clinical and biological data, such as computational methods for predicting disease phenotype from molecular and genetic profiling. New combined experimental and computational methods hold the promise of more accurate diagnosis and prognosis as well as more effective prevention and therapy.

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This paper delineates a few key questions that are fundamental and "on the table" for any approach into integrative bioinformatics:1. The importance of developing standards2.Data integration as the combination of heterogeneous biological data encoded with different semantics3. Semantics compatibility AND context resolution for correct data integration4.Achieving integration demands overcoming both technical and social challenges